Research Article
Is Vehicle Plate Corner Prediction by Vision Transformer Better than CNNs?
Table 2
The number of model parameters of selected ViT backbone models along with corresponding structural parameters.
| Model name | Patch size | Embedded dim | Depth | # of heads | # of param (m) |
| ViT-Patch-13 | 13 | 16 | 128 | 2 | 0.96 | ViT-Patch-26 | 26 | 32 | 128 | 2 | 1.9 | ViT-Patch-52 | 52 | 128 | 64 | 2 | 13.3 | ViT-Patch-104 | 104 | 128 | 128 | 8 | 26.8 | ViT-Patch-208 | 208 | 64 | 128 | 8 | 9.1 |
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